Electronic speech and text recognition and analysis for identifying computer-generated interactions

An audio analysis computing apparatus comprising:

• a processor;
• and
• memory storing computer-readable instructions that, when executed by the processor, causes the audio analysis computing apparatus to:
• detect an initiation of a voice call;
• receive an audio signal from the voice call, the audio signal comprising speech;
• analyze the audio signal using a first machine learning model, the first machine learning model configured to generate an audio speech score indicating a similarity between the speech in the audio signal and human speech;
• generate transcription text corresponding to the speech in the audio signal;
• analyze the transcription text using a second machine learning model, the second machine learning model configured to generate a transcribed text score indicating a similarity between the transcription text and language used by a human;
• determine an initial interaction score for the audio signal by combining the audio speech score and the transcribed text score, the initial interaction score indicating a likelihood that the audio signal is computer-generated;
• monitor a duration of the voice call;
• generate a duration score, the duration score indicating a likelihood that the voice call is computer-generated by comparing the duration of the voice call with an expected duration for the voice call;
• determine a composite interaction score for the voice call based on the initial interaction score and the duration score;
• determine whether the composite interaction score is greater than a first threshold score;
• and
• in response to determining that the composite interaction score is greater than the first threshold score, generate and transmit a command to a voice call device different from the audio analysis computing apparatus, the command configured to cause the voice call device to terminate the voice call.

A non-transitory computer-readable medium storing computer-readable instructions that, when executed cause a speech and text analysis apparatus to:

• detect an initiation of a voice call;
• receive an audio signal from the voice call, the audio signal comprising speech;
• analyze the audio signal using a first machine learning model, the first machine learning model configured to generate an audio speech score indicating a similarity between the speech in the audio signal and human speech;
• generate transcription text corresponding to the speech in the audio signal;
• analyze the transcription text using a second machine learning model, the second machine learning model configured to generate a transcribed text score indicating a similarity between the transcription text and language used by a human;
• determine an initial interaction score for the audio signal by combining the audio speech score and the transcribed text score, the initial interaction score indicating a likelihood that the audio signal is computer-generated;
• monitor a duration of the voice call;
• generate a duration score, the duration score indicating a likelihood that the voice call is computer-generated by comparing the duration of the voice call with an expected duration for the voice call;
• determine a composite interaction score for the voice call based on the initial interaction score and the duration score;
• determine whether the composite interaction score is greater than a first threshold score;
• and
• in response to determining that the composite interaction score is greater than the first threshold score, generate and transmit a command to a voice call device different from the speech analysis platform, the command configured to cause the voice call device to terminate the voice call.